The power curve provides a basis for predicting adjustments that animals make in flight speed, for example in relation to wind, distance, habitat foraging quality and objective. However, relatively few studies have examined how animals respond to the landscape below them, which could affect speed and power allocation through modifications in climb rate and perceived predation risk. We equipped homing pigeons ( Columba livia ) with high-frequency loggers to examine how flight speed, and hence effort, varies in relation to topography and land cover. Pigeons showed mixed evidence for an energy-saving strategy, as they minimized climb rates by starting their ascent ahead of hills, but selected rapid speeds in their ascents. Birds did not modify their speed substantially in relation to land cover, but used higher speeds during descending flight, highlighting the importance of considering the rate of change in altitude before estimating power use from speed. Finally, we document an unexpected variability in speed and altitude over fine scales; a source of substantial energetic inefficiency. We suggest this may be a form of protean behaviour adopted to reduce predation risk when flocking is not an option, and that such a strategy could be widespread.

For fast-flying birds, the ability to respond to wind during landing is critical, as errors can lead to injury or even death. Nonetheless, landing ability, and its ecological significance, remain unstudied. We show that for auks, 60% of attempts to land at their cliff nests fail in a strong breeze (80% in near-gale winds). This is most likely because wind interferes with the ability to maintain flight control in the last phase of landing. Their extreme flight costs mean that the energetic penalty for multiple landing attempts is high. We propose that exposure, and ability to respond to, such conditions will influence the suitability of breeding habitat. In support of this (i) auk colonies appear to be orientated away from prevailing winds and (ii) landing success within colonies is higher on crowded ledges with more airspace for manoeuvring. More generally, the interplay between wind and flight capacities could impact breeding distributions across species and scales.

All animals that operate within the atmospheric boundary layer need to respond to aerial turbulence. Yet little is known about how flying animals do this because evaluating turbulence at fine scales (tens to approx. 300 m) is exceedingly difficult. Recently, data from animal-borne sensors have been used to assess wind and updraft strength, providing a new possibility for sensing the physical environment. We tested whether highly resolved changes in altitude and body acceleration measured onboard solo-flying pigeons (as model flapping fliers) can be used as qualitative proxies for turbulence. A range of pressure and acceleration proxies performed well when tested against independent turbulence measurements from a tri-axial anemometer mounted onboard an ultralight flying the same route, with stronger turbulence causing increasing vertical displacement. The best proxy for turbulence also varied with estimates of both convective velocity and wind shear. The approximately linear relationship between most proxies and turbulence levels suggests this approach should be widely applicable, providing insight into how turbulence changes in space and time. Furthermore, pigeons were able to fly in levels of turbulence that were unsafe for the ultralight, paving the way for the study of how freestream turbulence affects the costs and kinematics of animal flight.

Recent work has highlighted that 'energy landscapes' should affect animal movement trajectories although expected patterns are rarely quantified. We developed a model, incorporating speed, substrate, superstrate and terrain slope, to determine minimized movement costs for an energetically well-understood model animal, Homo sapiens, negotiating an urban environment, to highlight features that promote increased tortuosity and affect area use. The model showed that high differential travel power costs between adjacent areas, stemming from substantial environmental heterogeneity in the energy landscape, produced the most tortuous least-cost paths across scales. In addition, projected territory size and shape in territorial animals is likely to be affected by the details in the energy landscape. We suggest that cognisance of energy landscapes is important for understanding animal movement patterns and that energetic differences between least cost- and observed pathways might code for, and give an explicit value to, other important landscape-use factors, such as the landscape of fear, food availability or social effects.

Body-mounted accelerometers provide a new prospect for estimating power use in flying birds, as the signal varies with the two major kinematic determinants of aerodynamic power: wingbeat frequency and amplitude. Yet wingbeat frequency is sometimes used as a proxy for power output in isolation. There is, therefore, a need to understand which kinematic parameter birds vary and whether this is predicted by flight mode (e.g. accelerating, ascending/descending flight), speed or morphology. We investigate this using high-frequency acceleration data from (i) 14 species flying in the wild, (ii) two species flying in controlled conditions in a wind tunnel and (iii) a review of experimental and field studies. While wingbeat frequency and amplitude were positively correlated, R 2 values were generally low, supporting the idea that parameters can vary independently. Indeed, birds were more likely to modulate wingbeat amplitude for more energy-demanding flight modes, including climbing and take-off. Nonetheless, the striking variability, even within species and flight types, highlights the complexity of describing the kinematic relationships, which appear sensitive to both the biological and physical context. Notwithstanding this, acceleration metrics that incorporate both kinematic parameters should be more robust proxies for power than wingbeat frequency alone.